What Should a Robot Do? Comparing Human and Large Language Model Recommendations for Robot Deception

被引：0

作者：

Rogers, Kantwon ^{[1
]}

Webber, Reiden John Allen ^{[1
]}

Zubizarreta, Geronimo Gorostiaga ^{[1
]}

Cruz, Arthur Melo ^{[2
]}

Chen, Shengkang ^{[1
]}

Arkin, Ronald C. ^{[1
]}

Borenstein, Jason ^{[1
]}

Wagner, Alan R. ^{[2
]}

机构：

[1] Georgia Inst Technol, Atlanta, GA 30332 USA

[2] Penn State Univ, State Coll, PA 16802 USA

来源：

COMPANION OF THE 2024 ACM/IEEE INTERNATIONAL CONFERENCE ON HUMAN-ROBOT INTERACTION, HRI 2024 COMPANION | 2024年

基金：

美国国家科学基金会;

关键词：

deception; ethical dilemmas; LLM; human-robot interaction;

D O I：

10.1145/3610978.3640752

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

This study compares human ethical judgments with Large Language Models (LLMs) on robotic deception in various scenarios. Surveying human participants and querying LLMs, we presented ethical dilemmas in high-risk and low-risk contexts. Findings reveal alignment between humans and LLMs in high-risk scenarios, prioritizing safety, but notable divergences in low-risk situations, refecting challenges in AI development to accurately capture human social nuances and moral expectations.

引用

页码：906 / 910

页数：5

共 28 条

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